Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability.

Journal: Skeletal radiology
Published Date: Feb 1, 2019

Abstract

OBJECTIVE: Radiographic bone age assessment (BAA) is used in the evaluation of pediatric endocrine and metabolic disorders. We previously developed an automated artificial intelligence (AI) deep learning algorithm to perform BAA using convolutional neural networks. We compared the BAA performance of a cohort of pediatric radiologists with and without AI assistance.

Authors

  • Shahein H Tajmir
    Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
  • Hyunkwang Lee
    Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
  • Randheer Shailam
    Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
  • Heather I Gale
    The Billings Clinic, Billings, MT, USA.
  • Jie C Nguyen
    Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Sjirk J Westra
    Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
  • Ruth Lim
    Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
  • Sehyo Yune
    Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
  • Michael S Gee
    Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
  • Synho Do
    Department of Radiology, Massachusetts General Hospital, Boston, MA, USA. sdo@mgh.harvard.edu.

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